1. Field of the Invention
The present invention relates to a demand forecasting method, system, and computer readable storage medium, and, more particularly, to demand forecasting system, and computer readable storage medium, with periodic fluctuation in consideration.
2. Description of the Related Art
Supplying commodities to a customer requires adequate inventory management of the commodities. Adequate commodity inventory management can suppress an inventory loss due to excessive inventory and opportunity loss originating from inventory deficiency.
A demand forecasting method and a demand forecasting program which can efficiently and adequately forecast a demand for a commodity, are disclosed in, for example, Unexamined Japanese Patent Application KOKAI Publication No. 2004-234471. According to the technique described in the Japanese publication, a management computer calculates a trend function based on the trend of demands (demand trend) by applying a growth model to an accumulation trend of the demands. Next, the management computer calculates the difference trend, which is the trend of a difference between the demand trend and the trend function. The management computer then calculates the periodic tune intensity of the difference trend using a Periodgram. When a periodicity is determined based on the tune intensity, the management computer approximates the difference between the demand trend and the trend function using a periodic function. The periodic function is calculated from a quadratic sine function comprising a quadratic function and a trigonometric function. The management computer then performs demand forecasting using a periodic function which is the combination of the trend function and the periodic function.
However, the technique described in the Japanese publication has the following problem. The trend function based on the Weibull growth model does not take negative values, while the periodic function based on the quadratic sine model may result in negative demand forecasting. Specifically, as shown in FIG. 22, when the level of the periodic function on the negative side exceeds the trend function, demand forecasting becomes negative.
The technique described in the Japanese publication has the following additional problem. When a commodity has been supplied over a very long period of time, there may not be a record of demand data since the time the commodity was first supplied. In such a case, demand forecasting is done based on the latest demand trend. A curve representing the trend function in that case may have a descending curve (ie., the amplitude descends with time) as shown in FIG. 23A. For a trend function having such a descending curve, the influence of the quadratic function of the quadratic sine model may cause the amplitude of the curve representing the demand forecasting model to forecast a larger value, as shown in FIG. 23B (in this case, forecast values appear on the right hand side after the vertical line at month 60).
With the quadratic sine function in use, when the positive/negative sign of the curve representing the quadratic function changes, the period may be shifted. That is, when the positive/negative sign of the curve representing the quadratic function is inverted, as shown in FIG. 24, the multiplication of the absolute value of the quadratic function and the sine function causes the phase to be shifted. This may result in unnatural forecasting.
Further, seasonal changes bring about cases that show features unique to commodities. For example, as shown in FIGS. 25A to 25C, the demanded quantity has peaks in some specific months. There is a case where the shapes of repetitive peaks are almost the same. When the sine function described in the Japanese publication is used, however, such features unique to commodities cannot be expressed. There is a demand for a seasonal change forecasting model capable of coping with such a change as having peak demand values only in specific months.
The invention has been made to overcome the problems. It is an object of the invention to provide a demand forecasting method, system, and computer readable storage medium, which can efficiently and adequately forecast a demand in consideration of a periodic change of a predetermined commodity.